Automated response system using smart data

ABSTRACT

Aspects of the disclosure relate to analyzing smart data using an automated response system. A computing platform may receive, from a user device, user feedback information comprising user feedback corresponding to an enterprise organization. Thereafter, the computing platform may identify, based on the user feedback information, identification information comprising a sender of the user feedback and an issue corresponding to the user feedback. Then, the computing platform may retrieve, from a hierarchical rules server and based on the identification information, hierarchy information comprising a hierarchy ranking of a plurality of automated responses. Subsequently, the computing platform may determine, based on analyzing the hierarchy information and the user feedback, an automated response from the plurality of automated responses. Next, the computing platform may generate one or more commands directing an external response server to execute the automated response. Then, the computing platform may transmit the one or more commands.

BACKGROUND

Aspects of the disclosure relate to data processing, artificialintelligence, knowledge processing, and computer-implemented rule-basedreasoning having specific pattern matching or control techniques. Inparticular, one or more aspects of the disclosure relates to analyzingsmart data using an automated response system.

In some instances, a support system for an enterprise organization mayreceive user feedback about the enterprise organization. The userfeedback may describe a vast range of issues, and the system may solveeach issue differently. As the enterprise organization grows morecomplex, the amount of user feedback, including the amount of issues andsolutions associated with the user feedback, may increase exponentially.Therefore, the system may have difficulty identifying connectionsbetween user feedback information as the amount of user feedbackincreases. Further, the system may have difficulty leveraging the userfeedback information to identify new and different solutions for thevast range of issues.

SUMMARY

Aspects of the disclosure provide effective, efficient, scalable, andconvenient technical solutions that address and overcome the technicalproblems associated with analyzing smart data using an automatedresponse system.

In accordance with one or more embodiments, a computing platform havingat least one processor, a memory, and a communication interface mayreceive, by the at least one processor, via the communication interface,and from a user device, user feedback information comprising userfeedback corresponding to an enterprise organization. Thereafter, thecomputing platform may identify, based on the user feedback information,identification information comprising a sender of the user feedback andan issue corresponding to the user feedback. Then, the computingplatform may retrieve, from a hierarchical rules server and based on theidentification information, hierarchy information comprising a hierarchyranking of a plurality of automated responses. Subsequently, thecomputing platform may determine, based on analyzing the hierarchyinformation and the user feedback, an automated response from theplurality of automated responses. Next, the computing platform maygenerate, by the at least one processor, one or more commands directingan external response server to execute the automated response. Then, thecomputing platform may transmit, via the communication interface and tothe external response server, the one or more commands directing anexternal response server to execute the automated response.

In some embodiments, the computing platform may retrieve, from thehierarchical rules server and based on the identification information,historical information corresponding to the sender of the user feedback.Subsequently, the determining the automated response from the pluralityof automated responses may be further based on the historicalinformation. In some embodiments, the historical information maycomprise information indicating a number of times the sender of the userfeedback submitted previous user feedback associated with the issue. Insome embodiments, the historical information of the issue may comprisehistorical information from a plurality of user feedback and from aplurality of different senders.

In some embodiments, the computing platform may determine, based on theuser feedback information, a biometric factor corresponding to the userfeedback. Subsequently, the determining the automated response from theplurality of automated responses may be based on the biometric factor.In some embodiments, the receiving the user feedback information maycomprise receiving the user feedback information from the user devicevia an email feedback system, a text feedback system, or an interactivevoice response feedback system.

In some embodiments, the hierarchy information may further comprise ahierarchy ranking of a plurality of issues. Subsequently, the computingplatform may determine, based on comparing the issue with the hierarchyranking of the plurality of issues, the hierarchy ranking of the issue.Then, the determining the automated response from the plurality ofautomated responses may be further based on the hierarchy ranking of theissue. In some embodiments, the computing platform may receive, via thecommunication interface and from the external response server, a statusof the user feedback. Subsequently, the computing platform may change,based on the status of the user feedback, the automated response in thehierarchy ranking of the plurality of automated responses.

In some embodiments, the computing platform may generate a web userinterface corresponding to the user feedback, wherein the web userinterface indicates the automated response and a status update for theuser feedback. Subsequently, the computing platform may transmit, viathe communication interface and to the user device, the web userinterface.

In some embodiments, the computing platform may determine a trend foreach of the plurality of automated responses, wherein the trendcorresponds to an efficiency of a corresponding automated response fromthe plurality of automated responses. Thereafter, the computing platformmay change, based on the trend for each of the plurality of automatedresponses, the hierarchy ranking of the plurality of automatedresponses.

These features, along with many others, are discussed in greater detailbelow.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is illustrated by way of example and not limitedin the accompanying figures in which like reference numerals indicatesimilar elements and in which:

FIGS. 1A, 1B, and 1C depict an illustrative computing environment foranalyzing smart data using an automated response system in accordancewith one or more example embodiments;

FIGS. 2A, 2B, 2C, 2D, and 2E depict an illustrative event sequence foranalyzing smart data using an automated response system in accordancewith one or more example embodiments;

FIGS. 3 and 4 depict example graphical user interfaces for analyzingsmart data using an automated response system in accordance with one ormore example embodiments; and

FIG. 5 depicts an illustrative method for analyzing smart data using anautomated response system in accordance with one or more exampleembodiments.

DETAILED DESCRIPTION

In the following description of various illustrative embodiments,reference is made to the accompanying drawings, which form a parthereof, and in which is shown, by way of illustration, variousembodiments in which aspects of the disclosure may be practiced. It isto be understood that other embodiments may be utilized, and structuraland functional modifications may be made, without departing from thescope of the present disclosure.

It is noted that various connections between elements are discussed inthe following description. It is noted that these connections aregeneral and, unless specified otherwise, may be direct or indirect,wired or wireless, and that the specification is not intended to belimiting in this respect.

FIGS. 1A and 1B depict an illustrative computing environment foranalyzing smart data using an automated response system in accordancewith one or more example embodiments. Referring to FIG. 1A, computingenvironment 100 may include one or more computing devices and/or othercomputer systems. For example, computing environment 100 may include anautomated response computing platform 110, a hierarchical rules server120, a user device 130, an email feedback system 140, a text feedbacksystem 150, an interactive voice response (IVR) feedback system 160, anadministrative device 170, and/or an external response system 180.

Automated response computing platform 110 may be configured to analyzeuser feedback and smart data by controlling and/or directing actions ofother devices and/or computer systems, and/or perform other functions,as discussed in greater detail below. In some instances, automatedresponse computing platform 110 may perform and/or provide one or moretechniques to analyze user feedback and smart data.

Hierarchical rules server 120 may be configured to store and/or maintainhierarchical rules information to analyze user feedback and smart data.For example, hierarchical rules server 120 may be configured to storeand/or maintain hierarchy information corresponding to clients, issues,actions in response to issues, and/or historical user information. Insome instances, the hierarchical rules server 120 might not be anotherentity, but the functionalities of the hierarchical rules server 120 maybe included within the automated response computing platform 110.

User device 130 may be configured to be used by one or more users ofcomputing environment 100. For example, the user device 130 may beconfigured to display, present, and/or otherwise provide one or moreuser interfaces that enable one or more users to provide user feedbackcorresponding to an enterprise organization. The user device 130 mayreceive, from the one or more users, user input or selections. Further,the user device 130 may send the user input or selections to theautomated response computing platform 110 and/or one or more othercomputer systems and/or devices in computing environment 100. The userdevice 130 may receive, from the automated response computing platform110 and/or one or more other computer systems and/or devices incomputing environment 100, information or data in response to the userinput or selection.

In some examples, the user device 130 may receive, from one or moreusers, user feedback information indicating feedback corresponding to anenterprise organization. After receiving the user feedback informationfrom the user, the user device 130 may transmit the user feedbackinformation to an email feedback system 140, a text feedback system 150,and/or an interactive voice response (IVR) feedback system 160. In someembodiments, the user device 130 may include a microphone and/or voicerecording system. For example, the microphone and/or voice recordingsystem may be used to record a voice recording from the user. The voicerecording may be a recorded voice message of the user feedback.

Email feedback system 140 may be configured to receive and transmit userfeedback information. For example, the user device 130 may transmit oneor more emails to the email feedback system 140. The emails may indicateuser feedback corresponding to the enterprise organization. The emailfeedback system 140 may receive the emails from the user device 130 andmay transmit the emails to the automated response computing platform110. In some instances, the email feedback system 140 may receive aplurality of emails from a plurality of different user devices. Eachuser device, such as user device 130, may correspond to a differentuser.

Text feedback system 150 may be configured to receive and transmit userfeedback information. For example, the user device 130 may transmit oneor more text messages to the text feedback system 150. The text messagesmay indicate user feedback corresponding to the enterprise organization.The text feedback system 150 may receive the text messages from the userdevice 130 and may transmit the text messages to the automated responsecomputing platform 110. In some instances, the text feedback system 150may receive a plurality of text messages from a plurality of differentuser devices. Each user device, such as user device 130, may correspondto a different user.

Interactive voice response (IVR) feedback system 160 may be configuredto receive and transmit user feedback information. For example, the userdevice 130 may transmit one or more voice messages to the IVR feedbacksystem 160. The voice messages may indicate user feedback correspondingto the enterprise organization. The IVR feedback system 160 may receivethe voice messages from the user device 130, and may convert the voicemessages into text. Additionally, and/or alternatively, the IVR feedbacksystem 160 may transmit the converted text messages to the automatedresponse computing platform 110. In some instances, the IVR feedbacksystem 160 may receive a plurality of voice messages from a plurality ofdifferent user devices. Each user device, such as user device 130, maycorrespond to a different user.

Administrative device 170 may be configured to be used by one or moreusers of computing environment 100. For example, the administrativedevice 170 may be configured to display, present, and/or otherwiseprovide one or more user interfaces that enable a user (e.g., anadministrator) to monitor a status of the user feedback. Theadministrative device 170 may receive, from the one or moreadministrators, user input or selections and send the user input orselections to the automated response computing platform 110 and/or oneor more other computer systems and/or devices in computing environment100. The administrative device 170 may receive, from the automatedresponse computing platform 110 and/or one or more other computersystems and/or devices in computing environment 100, information or datain response to the user input or selection.

External response system 180 may be a computing system configured tooffer any desired service, and may execute an automated response. Forexample, the external response system 180 may execute an automatedresponse based on the user feedback. Additionally, and/or alternatively,external response system 180 may provide one or more interfaces thatfacilitate communications with other systems (e.g., automated responsecomputing platform 110, hierarchical rules server 120, a user device130, an email feedback system 140, a text feedback system 150, IVRfeedback system 160, an administrative device 170, and an externalresponse system 180) in computing environment 100. In some instances,the external response system 180 may receive, from the automatedresponse computing platform 110, one or more commands to execute anautomated response based on the user feedback, as discussed in greaterdetail below. In some examples, the external response system 180 mayinclude a plurality of automated response systems, and each automatedresponse system may execute a plurality of different automated responsesbased on the user feedback.

In one or more arrangements, hierarchical rules server 120, user device130, email feedback system 140, text feedback system 150, IVR feedbacksystem 160, administrative device 170, and/or external response system180 may be any type of computing device capable of providing a userinterface, receiving input via the user interface, and communicating thereceived input to one or more other computing devices. For example,hierarchical rules server 120, user device 130, email feedback system140, text feedback system 150, IVR feedback system 160, administrativedevice 170, and/or external response system 180 may, in some instances,be and/or include server computers, desktop computers, laptop computers,tablet computers, smart phones, or the like that may include one or moreprocessors, memories, communication interfaces, storage devices, and/orother components. As noted above, and as illustrated in greater detailbelow, any and/or all of hierarchical rules server 120, user device 130,email feedback system 140, text feedback system 150, IVR feedback system160, administrative device 170, and/or external response system 180 may,in some instances, be special-purpose computing devices configured toperform specific functions.

Computing environment 100 also may include one or more computingplatforms. For example, and as noted above, computing environment 100may include the automated response computing platform 110. Asillustrated in greater detail below, the automated response computingplatform 110 may include one or more computing devices configured toperform one or more of the functions described herein. For example, theautomated response computing platform 110 may include one or morecomputers (e.g., laptop computers, desktop computers, servers, serverblades, or the like).

Computing environment 100 also may include one or more networks, whichmay interconnect one or more of automated response computing platform110, hierarchical rules server 120, user device 130, email feedbacksystem 140, text feedback system 150, IVR feedback system 160,administrative device 170, and/or external response system 180. Forexample, computing environment 100 may include network 190. Network 190may include one or more sub-networks (e.g., local area networks (LANs),wide area networks (WANs), or the like). For example, network 190 mayinclude a private sub-network that may be associated with a particularorganization (e.g., a corporation, financial institution, educationalinstitution, governmental institution, or the like) and that mayinterconnect one or more computing devices associated with theorganization. For example, automated response computing platform 110,hierarchical rules server 120, user device 130, email feedback system140, text feedback system 150, IVR feedback system 160, administrativedevice 170, and/or external response system 180 may be associated withan enterprise organization, and a private sub-network included innetwork 190 and associated with and/or operated by the organization mayinclude one or more networks (e.g., LANs, WANs, virtual private networks(VPNs), or the like) that interconnect automated response computingplatform 110, hierarchical rules server 120, user device 130, emailfeedback system 140, text feedback system 150, IVR feedback system 160,administrative device 170, and/or external response system 180. Network190 also may include a public sub-network that may connect the privatesub-network and/or one or more computing devices connected thereto(e.g., automated response computing platform 110, hierarchical rulesserver 120, user device 130, email feedback system 140, text feedbacksystem 150, IVR feedback system 160, administrative device 170, and/orexternal response system 180) with one or more networks and/or computingdevices that are not associated with the organization.

Referring to FIG. 1B, automated response computing platform 110 mayinclude one or more processors 111, memory 112, and communicationinterface 118. A data bus may interconnect processor(s) 111, memory 112,and communication interface 118. Communication interface 118 may be anetwork interface configured to support communication between theautomated response computing platform 110 and one or more networks(e.g., network 190). Memory 112 may include one or more program moduleshaving instructions that when executed by processor(s) 111 cause theautomated response computing platform 110 to perform one or morefunctions described herein and/or one or more databases that may storeand/or otherwise maintain information which may be used by such programmodules and/or processor(s) 111. In some instances, the one or moreprogram modules and/or databases may be stored by and/or maintained indifferent memory units of the automated response computing platform 110and/or by different computing devices that may form and/or otherwisemake up the automated response computing platform 110. For example,memory 112 may have, store, and/or include a data aggregation engine113, an issue routing engine 114, a user interface module 115, ananalytics module 116, and an autonomous response engine 117. Autonomousresponse engine 117 may include instructions that direct and/or causeautomated response computing platform 110 to analyze smart data and userfeedback to determine an automated response, as discussed in greaterdetail below.

Data aggregation engine 113 may aggregate data used by the autonomousresponse engine 117 and/or the automated response computing platform110. For example, after receiving the user feedback from the emailfeedback system 140, the text feedback system 150, and/or theinteractive voice response feedback system 160, the data aggregationengine 113 may aggregate the user feedback. In some embodiments, thedata aggregation engine 113 may store the user feedback used by theautonomous response engine 117 and/or the automated response computingplatform 110 in determining an automated response and/or in performingother functions.

Issue routing engine 114 may route issues used by the autonomousresponse engine 117 and/or the automated response computing platform110. For example, after receiving the user feedback from the emailfeedback system 140, the text feedback system 150, and/or theinteractive voice response feedback system 160, the issue routing engine114 may determine an issue corresponding to the user feedback. Based onthe issue, the issue routing engine 114 may route the issue to theexternal response system 180.

User interface module 115 may generate a user interface for the userdevice 130 and/or the administrative device 170. For example, afterreceiving the user feedback from the email feedback system 140, the textfeedback system 150, and/or the interactive voice response feedbacksystem 160, the user interface module 115 may generate an interactiveuser interface for the user feedback. In some embodiments, based on theissue and/or status of the user feedback, the user interface module 115may generate and update the user interface as the user feedback isanalyzed by the automated response computing platform 110.

Analytics module 116 may receive and use hierarchy information toanalyze the user feedback. For example, after receiving the userfeedback from the email feedback system 140, the text feedback system150, and/or the interactive voice response feedback system 160, theanalytics module 116 may receive hierarchy information from thehierarchical rules server 120. In some instances, based on the hierarchyinformation, the analytics module 116 may analyze and determine anautomated response for the user feedback.

Referring to FIG. 1C, hierarchical rules server 120 may include one ormore processors 121, memory 122, and communication interface 126. A databus may interconnect processor(s) 121, memory 122, and communicationinterface 126. Communication interface 126 may be a network interfaceconfigured to support communication between hierarchical rules server120 and one or more networks (e.g., network 190). Memory 122 may includeone or more program modules having instructions that when executed byprocessor(s) 121 cause the hierarchical rules server 120 to perform oneor more functions described herein and/or one or more databases that maystore and/or otherwise maintain information which may be used by suchprogram modules and/or processor(s) 121. In some instances, the one ormore program modules and/or databases may be stored by and/or maintainedin different memory units of the hierarchical rules server 120 and/or bydifferent computing devices that may form and/or otherwise make up thehierarchical rules server 120. For example, memory 122 may have, store,and/or include a hierarchical rules module 123, a hierarchical rulesdatabase 124, and a machine learning engine 125. Hierarchical rulesserver 120 may include instructions that direct and/or causehierarchical rules server 120 to analyze user feedback and smart data todetermine an automated response, as discussed in greater detail below.Hierarchical rules database 124 may store information used by thehierarchical rules module 123 and/or the hierarchical rules server 120in analyzing user feedback, smart data, and/or in performing otherfunctions. Machine learning engine 125 may have instructions that directand/or cause the hierarchical rules server 120 to set, define, and/oriteratively redefine optimization rules, techniques and/or otherparameters used by hierarchical rules server 120 and/or other systems incomputing environment 100.

FIGS. 2A, 2B, 2C, 2D, and 2E depict an illustrative event sequence foranalyzing smart data using an automated response system in accordancewith one or more example embodiments. Referring to FIG. 2A, at step 201,the user device 130 may transmit user feedback to the IVR feedbacksystem 160, the email feedback system 140, and/or the text feedbacksystem 150. For example, at step 201, the user device 130 may receiveuser feedback information from a user. FIG. 3 may display a sample userfeedback template. For instance, as shown in FIG. 3, graphical userinterface 300 may include one or more fields, controls, and/or otherelements that may allow a user to input user feedback information. Thegraphical user interface 300 may allow a user to input a sender,subject, and/or content of the user feedback. For example, the sendermay be the user (e.g., client of the enterprise organization)transmitting the user feedback. The subject may be a summary of thecorresponding content of the user feedback. Additionally, in someinstances, the subject may be a subject line of the email and/or textmessage. In some examples, the user feedback might not include a senderand/or subject. For example, the user device 130 may transmit an audioand/or an audiovisual file indicating the user feedback. The audioand/or audiovisual file might not include a subject and/or sender, butmay include a phone number and/or other identification associated withthe user device 130.

Further, the user feedback information may indicate informationcorresponding to user feedback about an enterprise organization. Forexample, a user, using the user device 130, may provide user feedbackcorresponding to the enterprise organization. User feedback may includesurveys, rating systems, and/or questions about the mobile application.Additionally, in some examples, the user feedback may include an issuecorresponding to the enterprise organization. The issue may indicate aproblem, dilemma, question and/or other feedback concerning theenterprise organization. For example, the user feedback may indicate anissue, such as that a user's password has expired. A support system forthe enterprise organization may use the user feedback information toassist the user in solving the issue indicated in the user feedback.

In some embodiments, the user device 130 may include text, email, and/orvoice recording capabilities. For example, the user feedback may be in aplurality of formats, including text, email, audio, and/or audiovisualfile formats. The user device 130 may receive the user feedbackinformation as text feedback, email feedback, voice recorded feedback,and/or video recorded feedback. For instance, a microphone and/or avoice recording system may assist the user device 130 to record a voicerecording of the user feedback. After user device 130 records the voicerecording of the user feedback, the user device 130 may transmit theuser feedback comprising the voice recording to the IVR feedback system160. Additionally, and/or alternatively, the user device 130 maytransmit user feedback information comprising textual information and/orother non-voice information. For example, the user device 130 maytransmit an email or text message indicating the user feedbackinformation to the email feedback system 140 and/or the text feedbacksystem 150. Further, in some instances, the user device 130 may includeonly a voice recording of the user feedback, a combination of a voicerecording of the user feedback and textual information and/or othernon-voice information, or only textual information and/or othernon-voice information.

At step 202, the automated response computing platform 110 may receivethe user feedback information from the email feedback system 140, thetext feedback system 150, and/or the IVR feedback system 160. In someexamples, after receiving the user feedback information, the automatedresponse computing platform 110 and/or the IVR feedback system mayconvert the user feedback, comprising the voice recording of the userfeedback, into text feedback. In some instances, the email feedbacksystem 140, the text feedback system 150, and/or the IVR feedback system160 may receive a plurality of user feedback from a plurality ofdifferent user devices. The plurality of different user devices may beassociated with the same user or a plurality of different users.

At step 203, the automated response computing platform 110 may identifyan issue corresponding to the user feedback. For example, afterreceiving the user feedback at step 202, the automated responsecomputing platform 110 may analyze the user feedback, such as thesender, subject and/or content of the user feedback, to identify anissue corresponding to the user feedback. In some embodiments, the userfeedback may correspond to a support request indicating an issue. Forexample, the user may submit a support request or a support ticket foran issue, such as the user cannot log on an account due to an expiredpassword. The automated response computing platform 110 may identify theissue, “expired password,” by analyzing the subject and/or text of thesupport request.

In some examples, the administrative device 170 may transmit a multitudeof known issues and/or problems corresponding to the enterpriseorganization. Each issue and/or problem may correspond with keywordsand/or synonyms of the keywords. For example, the term “expired” may bea keyword for “expired password.” Additionally, and/or alternatively,synonyms of “expired” may also be keywords used to identify the issue as“expired password.” The automated response computing platform 110 maystore, in memory 112, the multitude of issues corresponding to theenterprise organization. Then, after receiving the user feedback, theautomated response computing platform 110 may parse through the userfeedback for these keywords and/or synonyms. After identifying one ormore keywords and/or synonyms within the user feedback, the automatedresponse computing platform 110 may identify the issue from thecorresponding keyword and/or synonyms.

In some instances, the automated response computing platform 110 maycreate a new issue based on the subject and/or content of the userfeedback. For example, the automated response computing platform 110 maycreate a new issue from the subject and/or content of the user feedback.For instance, based on the phrases and/or words within the content ofthe user feedback (e.g., “does not work,” “problem area,” or “issue”),the automated response computing platform 110 may analyze the wordsand/or phrases, and create a new issue from the subject and/or contentof the user feedback. Additionally, in some embodiments, the automatedresponse computing platform 110 may parse through the user feedback andmight not determine any keywords and/or synonyms. In such situations,the automated response computing platform 110 may create a new issue forthe user feedback.

In some embodiments, the user feedback might not include a subject. Forexample, as mentioned earlier, the user feedback may be a voicerecording, such as an audio or an audiovisual file. The automatedresponse computing platform 110 may identify the issue from the contentof the voice recording (e.g., the converted text file associated withthe voice recording). Additionally, and/or alternatively, in someinstances, while the user device 130 may transmit user feedbackinformation including the sender and/or the subject, the automatedresponse computing platform 110 may eventually receive the user feedbackinformation without the sender and/or the subject. For example, theemail feedback system 140 may transmit the content of the user feedback,but due to an error, the email feedback system 140 might not transmitthe sender and/or subject of the user feedback. In such instances, theautomated response computing platform 110 may analyze the content of theuser feedback to identify the sender, subject, and/or issue of the userfeedback.

At step 204, the automated response computing platform 110 may identifya sender of the user feedback. For example, automated response computingplatform 110 may identify a sender of the user feedback based on anemail address, phone number, and/or other identification informationcorresponding to the user transmitting the user feedback. Referring backto FIG. 3, in some instances, the sender information may be easilyidentifiable in the user feedback. For example, the automated responsecomputing platform 110 may identify the sender from the email addressand/or phone number associated with the user feedback. In someembodiments, when the sender information is not easily identifiable, theautomated response computing platform 110 may analyze the user feedback,similar to step 203 above, to determine the sender of the user feedback.For example, the user feedback may be a text file that was convertedfrom a voice recording. The automated response computing platform 110may parse the user feedback (e.g., text file) to identify phrases and/orwords of the user feedback. For instance, the automated responsecomputing platform 110 may determine phrases from the user feedback(e.g., “My name is . . . ” or “My email is . . . ”) and use thesephrases to identify a sender of the user feedback.

Referring to FIG. 2B, at step 205, the automated response computingplatform 110 may determine biometric factors associated with the userfeedback. For example, the automated response computing platform 110 mayanalyze the user feedback to determine biometric factors for the userfeedback. In some examples, the automated response computing platform110 may parse through the user feedback to determine words and/orphrases of the user feedback associated with the biometric factors.Additionally, and/or alternatively, the automated response computingplatform 110 may determine the biometric factor based on the issue ofthe user feedback. For example, some issues, such as “employeeappreciation,” may be associated with a good or “happy” biometricfactor, whereas some issues, such as “lost driver's license” or “lostpassport,” may be associated with a bad or “angry” biometric factor.

At step 206, the automated response computing platform 110 may generatean identifier for the user feedback. For example, at step 206, automatedresponse computing platform 110 may generate an identifier, such as atracking number, tracking identifier, and/or another identifier, for thereceived user feedback. In some instances, the automated responsecomputing platform 110 may generate the identifier based on whether thereceived user feedback is from the email feedback system 140, the textfeedback system 150, and/or the IVR feedback system 160. Further, insome embodiments, the automated response computing platform 110 may usethe identifier to track the user feedback. For instance, the user mayseek to track the status of the user feedback, such as a support ticket.The user, using user device 130, may transmit a request for a status ofthe user feedback, such as a request to determine whether the issue hasbeen resolved. The automated response computing platform 110 may use thegenerated identifier for the user feedback to determine the status ofthe user feedback. Then, the automated response computing platform 110may transmit the status of the user feedback to the user device 130.

At step 207, the automated response computing platform 110 may aggregatethe user feedback information. For example, automated response computingplatform 110 may receive a plurality of user feedback from a pluralityof different user devices. At step 207, the automated response computingplatform 110 may aggregate, using data aggregation engine 113, theplurality of user feedback based on the sender, issue, subject,biometric factors, and/or file format (e.g., email, text, audio, and/oraudiovisual). In some examples, the automated response computingplatform 110 may use the aggregated user feedback to determine theautomated response for the user feedback. For instance, the automatedresponse computing platform 110 may aggregate the user feedback from thesame sender, and determine an automated response based on the aggregateduser feedback.

Further, in some embodiments, the automated response computing platform110 may aggregate the received user feedback for the same issue (e.g.,“password expired”). In such embodiments, the automated responsecomputing platform 110 may determine an automated response for theaggregated user feedback with the same issue. Additionally, in someinstances, the automated response computing platform 110 may aggregatethe received user feedback for the same subject. For example, a chain ofemails may include the same subject line. The automated responsecomputing platform 110 may aggregate the chain of emails that includethe same subject line and determine an automated response for the chainof emails. Also, in some examples, the automated response computingplatform 110 may aggregate the user feedback using the biometricfactors. For example, many users may submit user feedback indicatingappreciation for employees of the enterprise organization. The automatedresponse computing platform 110 may aggregate the user feedbackassociated with the “happy” biometric factor, and then determine anautomated response based on the biometric factor.

At step 208, the automated response computing platform 110 may retrievehistorical information for the sender from the hierarchical rules server120. For example, a sender of the user feedback may be a client of theenterprise organization. The automated response computing platform 110may retrieve the historical information for the sender (e.g., client)based on the identified sender, identified issue, and/or subject of theuser feedback. In some instances, the historical information may includepreviously received user feedback from the sender (e.g., client). Forexample, the sender, using user device 130 and/or another user deviceassociated with the sender, may have previously transmitted userfeedback indicating one or more issues. The automated response computingplatform 110 may retrieve historical information, including the previoususer feedback from the sender. In some embodiments, the historicalinformation may include previously received user feedback related to thesubject. For example, the received user feedback at step 202 may be froma chain of emails, text messages, and/or corresponding voice messagesfrom the sender. The automated response computing platform 110 mayretrieve historical information, including the chain of emails, textmessages, and/or corresponding voice messages from the sender.

In some instances, the automated response computing platform 110 mayretrieve a previous automated response and/or a previous biometricfactor associated with the sender. For example, after receiving previoususer feedback, the automated response computing platform 110 may haveperformed an automated action or automated response. Additionally, theautomated response computing platform 110 may have associated thepreviously received user feedback with certain biometric factors.

Referring to FIG. 2C, at step 209, the automated response computingplatform 110 may retrieve historical information for the issue from thehierarchical rules server 120. For example, the automated responsecomputing platform 110 may retrieve the historical information for theissue based on the identified sender, identified issue, and/or subjectof the user feedback. In some examples, the historical information mayinclude previously received user feedback for the issue. For example,multiple senders may have transmitted a plurality of previous userfeedback about the issue. The automated response computing platform 110may retrieve historical information, including the plurality of previoususer feedback about the issue.

In some instances, the automated response computing platform 110 mayretrieve a previous automated response and/or a previous biometricfactor associated with the issue. For example, after receiving previoususer feedback, the automated response computing platform 110 may haveperformed an automated action or automated response. Additionally, theautomated response computing platform 110 may have associated previouslyreceived user feedback with certain biometric factors.

At step 210, the automated response computing platform 110 may retrievehierarchy information for issues. For example, at step 210, automatedresponse computing platform 110 may retrieve, from the hierarchicalrules server 120, hierarchy information for the issues. For instance,each issue may be treated differently based on the importance of theissue for the enterprise organization. Some issues may be more importantthan other issues, and the hierarchy information may indicate a higherpriority and/or a preference for the more important issues. Based on thehigher priority and/or preference, the hierarchical rules server 120 maycreate, monitor, and/or update a hierarchy ranking of issues using themachine learning engine 125. At step 210, the automated responsecomputing platform 110 may retrieve the hierarchy information indicatingthe hierarchy ranking of issues from the hierarchical rules server 120.

In some instances, after retrieving the hierarchy ranking of issues, theautomated response computing platform 110 may determine a position ofthe issue corresponding to the user feedback within the hierarchyranking of issues. For example, the hierarchy ranking of issues mayinclude the issues and a corresponding ranking associated with eachissue. After identifying the issue at step 203, the automated responsecomputing platform 110 may compare the identified issue with hierarchyranking of issues to determine the corresponding ranking of the issue.Additionally, and/or alternatively, in some examples, rather than acorresponding ranking associated with each issue, the ranking maycorrespond to a numerical (e.g., 1-100) and/or alphabetical (e.g., A-E)ranking. The automated response computing platform 110 may compare theidentified issue at step 203 with the hierarchy ranking of issues todetermine the numerical and/or alphabetical ranking of the issue. A highnumerical or alphabetical ranking (e.g., 90 or A) may correspond to ahigh priority issue, whereas a low numerical or alphabetical ranking(e.g., 20 or E) may correspond to a low priority issue.

At step 211, the automated response computing platform 110 may retrieve,from the hierarchical rules server 120, hierarchy information indicatingactions and/or responses for the issues. For example, based on theclient and/or the issue, the hierarchical rules server 120 may create ahierarchy of automated responses to address and/or solve the issues.Some of the automated responses may be more severe or effective thanothers. And, based on the severity and/or effectiveness of the automatedresponses, the hierarchical rules server 120 may create, update, and/ormonitor a hierarchy ranking of the automated responses using the machinelearning engine 125. For instance, more severe automated responses, suchas “contact supervisor,” may be higher ranked than less severe automatedresponses, such as “send reminder email.

In some instances, the automated responses may route the issueassociated with the user feedback to one or more external responsesystems 180. For example, the one or more external response systems 180may be a support system, such as a help desk, that resolves issues forthe enterprise organization. The external response systems 180 (e.g.,the support systems) may be ranked by their effectiveness in resolvingissues. Further, each external response systems 180 may perform uniqueactions and/or responses that range in severity. For instance, someexternal response systems 180 may perform more severe actions and/orresponses, whereas other external response systems 180 may perform lesssevere actions and/or responses. As explained below, after determiningthe automated response, the automated response computing platform 110may route, using the issue routing engine 114, the issue determined atstep 203, to one or more support systems associated with the enterpriseorganization.

At step 212, the automated response computing platform 110 may determinea subset of the actions and/or responses from the hierarchy of actionsand/or responses. For example, based on the ranking of the issue and/orthe historical information for the user feedback, the automated responsecomputing platform 110 may determine a subset of automated responsesfrom the hierarchy of automated responses. In some embodiments, a higherranked issue may be associated with a higher subset or part of thehierarchy ranking of the automated responses, whereas a lower rankedissue may indicate a lower subset or part of the hierarchy ranking ofautomated responses. Additionally, and/or alternatively, the automatedresponse computing platform 110 may use the historical information tonarrow the subset of automated responses.

In some instances, an automated response may be incompatible withparticular issues and/or clients. For example, the automated action of“contacting a supervisor” may be incompatible with the issue “lostpassport.” As such, the automated response computing platform 110 mayremove incompatible automated responses from the hierarchy ranking ofautomated responses prior to determining the subset of automatedresponses. Further, in some examples, an automated response may routethe issue to an external response system 180 that is not capable ofresolving the issue. As such, the automated response computing platform110 may remove automated responses that route issues to externalresponse systems 180 that are not capable of resolving the issue.

At step 213, the automated response computing platform 110 may determinean escalation of the user feedback. For example, after retrieving thehistorical information, the automated response computing platform 110may escalate the user feedback based on the number of times theautomated response computing platform 110 receives user feedbackindicating the same client and/or the same issue. For example, byescalating the user feedback, the automated response computing platform110 may move the subset of responses up the hierarchy ranking ofresponses. In some instances, the automated response computing platform110 may determine the number of times the automated response computingplatform 110 has received the user feedback indicating the same clientand/or the same issue. Afterwards, as explained below, the automatedresponse computing platform 110 may determine the automated response inthe subset based on the number of times the automated response computingplatform 110 received the user feedback.

Referring to FIG. 2D, at step 214, the automated response computingplatform 110 may determine trends associated with the user feedback. Forexample, the automated response computing platform 110 may analyze,using the analytics module 116, trends for the identified sender and/orclient, identified issue, historical information, and/or automatedresponses to issues. Based on the historical information (e.g., pastuser feedback), the trends may indicate the performance (e.g., success,failure, and/or efficiency) associated with the identified client,identified issue, and/or the automated responses. In some embodiments,the automated response computing platform 110 may determine theperformance by the number of received user feedback describing theparticular issue and/or the particular client over a period of time. Forexample, if the number surpasses a pre-defined threshold for a period oftime, the automated response computing platform 110 may determine thatthe actions and/or responses that are in response to the issue might notbe effective. Additionally, if the amount is below the pre-definedthreshold for a period of time, the automated response computingplatform 110 may determine the action and/or response that are inresponse to the issue may be effective.

In some instances, the automated response computing platform 110 maydetermine the trends for the identified client, the identified issue,and/or the identified automated response. For example, the automatedresponse computing platform 110 may determine the performance of theautomated responses for a plurality of issues. Based on the performance,the automated response computing platform 110 may determine thatparticular automated responses may be more or less effective forparticular issues. Additionally, and/or alternatively, the automatedresponse computing platform 110 may determine the performance of theautomated responses for a plurality of clients. Based on theperformance, the automated response computing platform 110 may thedetermine that particular automated responses may be more or lesseffective for particular clients. Also, the automated response computingplatform 110 may determine the trends for the automated responses. Forexample, the automated response computing platform 110 may determine theperformance of the automated response for a plurality of clients over aplurality of issues. Based on the performance, the automated responsecomputing platform 110 may the determine that the automated response maybe more or less effective for particular issues and/or particularclients.

At step 215, the automated response computing platform 110 may determinethe automated response for the user feedback. For example, the automatedresponse computing platform 110 may determine the automated responsebased on the determined subset of actions and/or responses, theescalation of user feedback, the biometric factor, and/or the trendsassociated with the user feedback. In some instances, the automatedresponse computing platform 110 may first determine whether to changethe subset of actions and/or responses based on the escalation of theuser feedback (e.g., moving up the subset of actions and/or responses inthe hierarchy ranking). Afterwards, the automated response computingplatform 110 may determine, from the trends at step 214, theeffectiveness for each of the actions and/or responses in the subset.The automated response computing platform 110 may determine the actionand/or response from the subset based on the trends for the identifiedissue and/or the identified client. In some examples, the automatedresponse computing platform 110 may determine the automated responseand/or action in the subset based on the number of times the automatedresponse computing platform 110 receives the user feedback indicatingthe client and/or issue. For instance, the automated response computingplatform 110 may select a different and/or more severe automatedresponse each time the automated response computing platform 110receives user feedback indicating the client and/or issue.

In some embodiments, the automated response computing platform 110 maydetermine the automated response in the subset based on the biometricfactor associated with the user feedback. For example, based on a “good”or “happy” biometric factor, the automated response computing platform110 may select a less severe automated response from the subset ofautomated responses. In other examples, based on a “bad” or “angry”biometric factor, the automated response computing platform 110 mayselect a more severe automated response.

In some instances, computing environment 100 may include a plurality ofdifferent external response systems 180. For example, the differentexternal response systems 180 may be associated with different supportsystems for the enterprise organization. Additionally, the differentexternal response systems 180 may be tasked with executing differentautomated responses. After determining the automated response, theautomated response computing platform 110 may determine the externalresponse system 180 that is tasked with executing the automatedresponse. Then, the automated response computing platform 110 may route,using the issue routing engine 114 and based on the factors listedabove, the issue and/or user feedback to the appropriate externalresponse system 180.

At step 216, the automated response computing platform 110 may transmitthe automated response. For example, after determining the automatedresponse, the automated response computing platform 110 may transmit oneor more commands directing the external response system 180 to executethe automated response. In some examples, the automated response mayroute the issue and/or the user feedback to the appropriate externalresponse system 180. Thus, at step 216, after determining theappropriate external response system 180, the automated responsecomputing platform 110 may transmit or route the user feedback, theissue, and/or additional actions and/or responses to the appropriateexternal response system 180.

At step 217, the automated response computing platform 110 may generatea user interface for the user feedback. For example, the automatedresponse computing platform 110 may generate, using the user interfacemodule 115, a user interface for the user feedback. As shown in FIG. 4,graphical user interface 400 may include one or more fields, controls,and/or other elements that may allow a user (e.g., an administratorand/or a user) to interact with links and/or identify informationassociated the user feedback. For example, the graphical user interface400 may allow a user and/or an administrator to use links and/or graphsto view the trend analysis 410, the graph of the trend analysis 420, thetracking identifier 430, the current status 440, the historical data forissue 450, and/or related issues from other users 460. The trendanalysis and/or the graph of the trend analysis 420 may correspond tothe determined trends associated with the user feedback at step 214. Thetracking identifier 430 may correspond with the generated trackingidentifier at step 206. The historical data for the issue 450 maycorrespond with the retrieved hierarchy information for the clients atstep 208 and/or the hierarchy information for user feedback at step 209.The related issue from other users 460 may correspond to the retrievedhierarchy information for issues at step 210. Using graphical userinterface 400, the user may be able to obtain real-time live updatescorresponding to the issue identified at step 203. Further, the currentstatus 440 may identify a status of the user feedback, such ascompleted, in progress, or need more assistance. Additionally, thecurrent status 440 may identify the automated response determined atstep 215. The administrator may use graphical user interface 400 todetermine the issue, automated response, and/or assess the performanceof the automated response.

Referring to FIG. 2E, at step 218, the automated response computingplatform 110 may determine a status of the user feedback based on theautomated response. In some instances, after transmitting the one ormore commands to execute the automated response, the automated responsecomputing platform 110 may monitor whether new user feedback indicatingthe identified client and/or the identified issue has been receivedwithin a pre-defined period of time. After receiving the new userfeedback indicating the identified client and/or issue, the automatedresponse computing platform 110 may determine the status of the userfeedback as not completed. However, when new user feedback indicatingthe identified client and/or issue has not been received in thepre-defined period of time, the automated response computing platform110 may determine the status of the user feedback as completed. Further,in some embodiments, the automated response computing platform 110 maymonitor whether new user feedback indicating the identified clientand/or the identified issue surpasses a pre-defined threshold. Based onmonitoring whether the new user feedback has been received in apre-defined period of time and/or whether the new user feedbacksurpasses a pre-defined threshold, the automated response computingplatform may update the performance for the automated response.

In some examples, after executing the determined automated response, theautomated response computing platform 110 may transmit a request to theuser device 130 and/or the administrative device 170 inquiring about thestatus. In response to the request, the automated response computingplatform 110 may receive, from the user device 130 and/or administrativedevice 170, an input indicating whether the issue has been completed, inprogress, or not resolved. For example, referring back to FIG. 4, theuser and/or administrator may select the current status link 440 toinput the current status of the user feedback.

At step 219, the automated response computing platform 110 may updatethe trends of the user feedback. For example, the automated responsecomputing platform 110 may determine a client, issue, automatedresponse, and/or status (e.g., performance) of the automated response asexplained above. Based on the status or performance of the automatedresponse, the automated response computing platform 110 may update,using the analytics module 116, the trends for the identified client,identified issue, and/or identified automated response. When theautomated response computing platform 110 receives a new user feedback,the automated response computing platform 110 may use the new andupdated trends to determine the automated response for the client and/orissue.

At step 220, the automated response computing platform 110 may generateone or more commands to update the hierarchy information based on theupdated trends at step 219. For example, the automated responsecomputing platform 110 may generate one or more commands to update thehierarchy information including the hierarchy ranking of the issuesand/or the automated responses based on the updated trends. At step 221,the automated response computing platform 110 may transmit the commandsto update the hierarchy information to the hierarchal rules server 120.The hierarchal rules server 120 may receive the commands, and using themachine learning engine 125, may continuously update the hierarchyinformation based on new user feedback.

By updating the trends at step 219, the hierarchy information may alsobe updated. For example, the automated response computing platform 110may analyze the status of the user feedback and may determine theautomated response caused a change in status (e.g., completed, inprogress, or not resolved). Then, the automated response computingplatform 110 may generate one or more commands to add, remove, and/orchange the hierarchy ranking of the issue and/or the automated responsesbased on the status or performance of the user feedback. For instance,the one or more commands may move the automated response in thehierarchy ranking of the automated responses up or down in the hierarchyranking. Additionally, and/or alternatively, after updating the trends,the automated response computing platform 110 may transmit these updatedtrends to the hierarchical rules server 120. After receiving thesecommands, the hierarchical rules server 120 may monitor and/or update,using machine learning engine 125, the hierarchy ranking for the issueand/or the automated responses. In some instances, after receiving thestatus of each user feedback, the hierarchical rules server 120 maymonitor and/or update the hierarchy ranking for the issue and/or theautomated responses. Thus, the hierarchical rules server 120 maycontinue to set, define, and/or iteratively redefine optimization rules,techniques and/or other parameters used by hierarchical rules server 120and/or the automated response computing platform 110 in determining theautomated responses. For example, the hierarchical rules server 120 maycontinuously add, change, and/or remove issues, and/or automatedresponses from the hierarchy rankings as user feedback is analyzed.

Further, in some embodiments, a particular client and/or a particularissue may be associated with an individual hierarchy ranking ofautomated responses. In such instances, the automated response computingplatform 110 may determine unique hierarchy rankings of automatedresponses for the particular clients and/or particular issues. Then, theautomated response computing platform 110 may add, remove, and/or changethe hierarchy ranking of the automated responses for particular clientsand/or issues based on the determined status. For example, the status ofthe user feedback may indicate “completed” for the particular clientand/or issue. The automated response computing platform 110 may add orchange (e.g., move up) the automated response in the hierarchy rankingof automated responses for the client and/or issue. In other examples,the status of the user feedback may indicate “not resolved” for theparticular client and/or issue. The automated response computingplatform 110 may remove or change (e.g., move down) the automatedresponse in the hierarchy ranking of automated responses for the clientand/or issue.

FIG. 5 depicts an illustrative method for analyzing smart data using anautomated response system in accordance with one or more exampleembodiments. Referring to FIG. 5, at step 505, a computing platformhaving at least one processor, a memory, and a communication interfacemay receive, by the at least one processor, via the communicationinterface, and from a user device, user feedback information comprisinguser feedback corresponding to an enterprise organization. At step 510,the computing platform may identify, based on the user feedbackinformation, identification information comprising a sender of the userfeedback and an issue corresponding to the user feedback. At step 515,the computing platform may retrieve, from a hierarchical rules serverand based on the identification information, hierarchy informationcomprising a hierarchy ranking of a plurality of automated responses. Atstep 520, the computing platform may determine, based on analyzing thehierarchy information and the user feedback, an automated response fromthe plurality of automated responses. At step 525, the computingplatform may generate, by the at least one processor, one or morecommands directing an external response server to execute the automatedresponse. At step 530, the computing platform may transmit, via thecommunication interface and to the external response server, the one ormore commands directing an external response server to execute theautomated response.

One or more aspects of the disclosure may be embodied in computer-usabledata or computer-executable instructions, such as in one or more programmodules, executed by one or more computers or other devices to performthe operations described herein. Generally, program modules includeroutines, programs, objects, components, data structures, and the likethat perform particular tasks or implement particular abstract datatypes when executed by one or more processors in a computer or otherdata processing device. The computer-executable instructions may bestored as computer-readable instructions on a computer-readable mediumsuch as a hard disk, optical disk, removable storage media, solid-statememory, RAM, and the like. The functionality of the program modules maybe combined or distributed as desired in various embodiments. Inaddition, the functionality may be embodied in whole or in part infirmware or hardware equivalents, such as integrated circuits,application-specific integrated circuits (ASICs), field programmablegate arrays (FPGA), and the like. Particular data structures may be usedto more effectively implement one or more aspects of the disclosure, andsuch data structures are contemplated to be within the scope of computerexecutable instructions and computer-usable data described herein.

Various aspects described herein may be embodied as a method, anapparatus, or as one or more computer-readable media storingcomputer-executable instructions. Accordingly, those aspects may takethe form of an entirely hardware embodiment, an entirely softwareembodiment, an entirely firmware embodiment, or an embodiment combiningsoftware, hardware, and firmware aspects in any combination. Inaddition, various signals representing data or events as describedherein may be transferred between a source and a destination in the formof light or electromagnetic waves traveling through signal-conductingmedia such as metal wires, optical fibers, or wireless transmissionmedia (e.g., air or space). In general, the one or morecomputer-readable media may be and/or include one or more non-transitorycomputer-readable media.

As described herein, the various methods and acts may be operativeacross one or more computing servers and one or more networks. Thefunctionality may be distributed in any manner, or may be located in asingle computing device (e.g., a server, a client computer, and thelike). For example, in alternative embodiments, one or more of thecomputing platforms discussed above may be combined into a singlecomputing platform, and the various functions of each computing platformmay be performed by the single computing platform. In such arrangements,any and/or all of the above-discussed communications between computingplatforms may correspond to data being accessed, moved, modified,updated, and/or otherwise used by the single computing platform.Additionally, or alternatively, one or more of the computing platformsdiscussed above may be implemented in one or more virtual machines thatare provided by one or more physical computing devices. In sucharrangements, the various functions of each computing platform may beperformed by the one or more virtual machines, and any and/or all of theabove-discussed communications between computing platforms maycorrespond to data being accessed, moved, modified, updated, and/orotherwise used by the one or more virtual machines.

Aspects of the disclosure have been described in terms of illustrativeembodiments thereof. Numerous other embodiments, modifications, andvariations within the scope and spirit of the appended claims will occurto persons of ordinary skill in the art from a review of thisdisclosure. For example, one or more of the steps depicted in theillustrative figures may be performed in other than the recited order,and one or more depicted steps may be optional in accordance withaspects of the disclosure.

What is claimed is:
 1. A computing platform, comprising: at least oneprocessor; a communication interface communicatively coupled to the atleast one processor; and memory storing computer-readable instructionsthat, when executed by the at least one processor, cause the computingplatform to: receive, by the at least one processor, via thecommunication interface, and from a user device, user feedbackinformation comprising user feedback corresponding to an enterpriseorganization; identify, based on the user feedback information,identification information comprising a sender of the user feedback andan issue corresponding to the user feedback; retrieve, from ahierarchical rules server and based on the identification information,hierarchy information comprising a hierarchy ranking of a plurality ofautomated responses; escalate the user feedback based on a number oftimes the sender of the user feedback submitted previous user feedbackassociated with the issue; in response to the escalating, move a subsetof the plurality of automated responses in the hierarchy ranking of theplurality of automated responses; determine, based on analyzing thehierarchy information and the user feedback, an automated response fromthe subset of the plurality of automated responses; generate, by the atleast one processor, one or more commands directing an external responseserver to execute the automated response; and transmit, via thecommunication interface and to the external response server, the one ormore commands directing an external response server to execute theautomated response.
 2. The computing platform of claim 1, wherein thememory stores additional computer-readable instructions that, whenexecuted by the at least one processor, further causes the computingplatform to: retrieve, from the hierarchical rules server and based onthe identification information, historical information corresponding tothe sender of the user feedback, and wherein the determining theautomated response from the plurality of automated responses is furtherbased on the historical information.
 3. The computing platform of claim1, wherein the memory stores additional computer-readable instructionsthat, when executed by the at least one processor, further causes thecomputing platform to: retrieve, from the hierarchical rules server andbased on the identification information, historical informationcorresponding to the issue, and wherein the determining the automatedresponse is further based on the historical information.
 4. Thecomputing platform of claim 3, wherein the historical information of theissue comprises historical information from a plurality of user feedbackand from a plurality of different senders.
 5. The computing platform ofclaim 1, wherein the memory stores additional computer-readableinstructions that, when executed by the at least one processor, furthercauses the computing platform to: determine, based on the user feedbackinformation, a biometric factor corresponding to the user feedback, andwherein the determining the automated response from the plurality ofautomated responses is based on the biometric factor.
 6. The computingplatform of claim 1, wherein the receiving the user feedback informationcomprises receiving the user feedback information from the user devicevia an email feedback system, a text feedback system, or an interactivevoice response feedback system.
 7. The computing platform of claim 1,wherein the hierarchy information further comprises a hierarchy rankingof a plurality of issues, and wherein the memory stores additionalcomputer-readable instructions that, when executed by the at least oneprocessor, further causes the computing platform to: determine, based oncomparing the issue with the hierarchy ranking of the plurality ofissues, the hierarchy ranking of the issue, and wherein the determiningthe automated response from the plurality of automated responses isfurther based on the hierarchy ranking of the issue.
 8. The computingplatform of claim 1, wherein the memory stores additionalcomputer-readable instructions that, when executed by the at least oneprocessor, further causes the computing platform to: receive, via thecommunication interface and from the external response server, a statusof the user feedback; and change, based on the status of the userfeedback, the automated response in the hierarchy ranking of theplurality of automated responses.
 9. The computing platform of claim 1,wherein the memory stores additional computer-readable instructionsthat, when executed by the at least one processor, further causes thecomputing platform to: generate a web user interface corresponding tothe user feedback, wherein the web user interface indicates theautomated response and a status update for the user feedback; andtransmit, via the communication interface and to the user device, theweb user interface.
 10. The computing platform of claim 1, wherein thememory stores additional computer-readable instructions that, whenexecuted by the at least one processor, further causes the computingplatform to: determine a trend for each of the plurality of automatedresponses, wherein the trend corresponds to an efficiency of acorresponding automated response from the plurality of automatedresponses; and change, based on the trend for each of the plurality ofautomated responses, the hierarchy ranking of the plurality of automatedresponses.
 11. The computing platform of claim 1, wherein the memorystores additional computer-readable instructions that, when executed bythe at least one processor, further causes the computing platform to:when the number of times exceeds a first predetermined threshold duringa first predetermined time duration, removing the subset of theplurality of automated responses from the plurality of automatedresponses for the issue.
 12. The computing platform of claim 1, whereinthe memory stores additional computer-readable instructions that, whenexecuted by the at least one processor, further causes the computingplatform to: when the number of times is less than a secondpredetermined threshold during a second predetermined time duration,retaining the subset of the plurality of automated responses from theplurality of automated responses for the issue.
 13. A method,comprising: at a computing platform comprising at least one processor,memory, and a communication interface: receiving, by the at least oneprocessor, via the communication interface, and from a user device, userfeedback information comprising user feedback corresponding to anenterprise organization; identifying, based on the user feedbackinformation, identification information comprising a sender of the userfeedback and an issue corresponding to the user feedback; retrieving,from a hierarchical rules server and based on the identificationinformation, hierarchy information comprising a hierarchy ranking of aplurality of automated responses; escalating the user feedback based ona number of times the sender of the user feedback submitted previoususer feedback associated with the issue; in response to the escalating,moving a subset of the plurality of automated responses in the hierarchyranking of the plurality of automated responses; determining, based onanalyzing the hierarchy information and the user feedback, an automatedresponse from the subset of the plurality of automated responses;generating, by the at least one processor, one or more commandsdirecting an external response server to execute the automated response;and transmitting, via the communication interface and to the externalresponse server, the one or more commands directing an external responseserver to execute the automated response.
 14. The method of claim 13,further comprising: retrieving, by the at least one processor, from thehierarchical rules server, and based on the identification information,historical information corresponding to the sender of the user feedback,and wherein the determining the automated response from the plurality ofautomated responses is further based on the historical information. 15.The method of claim 13, further comprising: retrieving, by the at leastone processor, from the hierarchical rules server, and based on theidentification information, historical information corresponding to theissue, and wherein the determining the automated response is furtherbased on the historical information.
 16. The method of claim 13, furthercomprising: determining, by the at least one processor and based on theuser feedback information, a biometric factor corresponding to the userfeedback, and wherein the determining the automated response from theplurality of automated responses is based on the biometric factor. 17.The method of claim 13, wherein the hierarchy information furthercomprises a hierarchy ranking of a plurality of issues, and wherein themethod further comprises: determining, by the at least one processor andbased on comparing the issue with the hierarchy ranking of the pluralityof issues, the hierarchy ranking of the issue, and wherein thedetermining the automated response from the plurality of automatedresponses is further based on the hierarchy ranking of the issue. 18.The method of claim 13, further comprising: determining, by the at leastone processor, a trend for each of the plurality of automated responses,wherein the trend corresponds to an efficiency of a correspondingautomated response from the plurality of automated responses; andchanging, by the at least one processor and based on the trend for eachof the plurality of automated responses, the hierarchy ranking of theplurality of automated responses.
 19. The method of claim 13, furthercomprising: generating a web user interface corresponding to the userfeedback, wherein the web user interface indicates the automatedresponse and a status update for the user feedback; and transmitting,via the communication interface and to the user device, the web userinterface.
 20. One or more non-transitory computer-readable mediastoring instructions that, when executed by a computing platformcomprising at least one processor, memory, and a communicationinterface, cause the computing platform to: receive, by the at least oneprocessor, via the communication interface, and from a user device, userfeedback information comprising user feedback corresponding to anenterprise organization; identify, based on the user feedbackinformation, identification information comprising a sender of the userfeedback and an issue corresponding to the user feedback; retrieve, froma hierarchical rules server and based on the identification information,hierarchy information comprising a hierarchy ranking of a plurality ofautomated responses; escalate the user feedback based on a number oftimes the sender of the user feedback submitted previous user feedbackassociated with the issue; in response to the escalating, move a subsetof the plurality of automated responses in the hierarchy ranking of theplurality of automated responses; determine, based on analyzing thehierarchy information and the user feedback, an automated response fromthe subset of the plurality of automated responses; generate, by the atleast one processor, one or more commands directing an external responseserver to execute the automated response; and transmit, via thecommunication interface and to the external response server, the one ormore commands directing an external response server to execute theautomated response.